Apparatus and methods for optimization of integrated circuits

ABSTRACT

A system for computer-aided design (CAD) of an integrated circuit (IC) uses a computer. The computer is configured to optimize placement, routing, and/or region configuration of the integrated circuit (IC) by maximizing a number of low-power regions in the integrated circuit (IC).

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application claims priority to, and incorporates byreference, U.S. Provisional Patent Application Ser. No. 60/976,972,filed on Oct. 2, 2007, titled “Apparatus and methods for high-speedlow-power region optimization.”

TECHNICAL FIELD

The disclosed concepts relate generally to optimizing the performance ofintegrated circuits (ICs), such as programmable logic devices (PLDs).More particularly, disclosed concepts concern optimizing powerconsumption of ICs, for example, PLDs.

BACKGROUND

Advances in electronics has allowed increased level of integration. Thetechnology for fabrication of ICs has contributed to those advances, andhas provided a vehicle for integrating a relatively large number ofcircuits and functions into an IC. As a result, present-day ICs mightcontain hundreds of millions of transistors. Consequently, the powerconsumption, power dissipation, die temperatures and, hence, powerdensity (power dissipation in various circuits or blocks), of ICs hastended to increase. The upward march of the power density might make ICdesign and implementation impractical or failure-prone.

SUMMARY

The disclosed concepts relate to apparatus and methods for poweroptimization in electronic circuits, such as programmable logic devices(PLDs). In one exemplary embodiment, a system for computer-aided design(CAD) of an integrated circuit (IC) includes a computer. The computer isconfigured to optimize synthesis, placement, and/or routing of the IC bymaximizing a number of low-power regions in the IC. In another exemplaryembodiment, a CAD system for the design of an IC includes a computer.The computer is configured to set each region in a plurality of regionsin the IC to operate in one of at least two modes in order to optimizetiming and power consumption of the IC. The two modes include alow-power mode of operation and a high-speed mode of operation.

BRIEF DESCRIPTION OF THE DRAWINGS

The appended drawings illustrate only exemplary embodiments andtherefore should not be considered as limiting its scope. Persons ofordinary skill in the art who have the benefit of this disclosureappreciate that the disclosed concepts lend themselves to other equallyeffective embodiments. In the drawings, the same numeral designatorsused in more than one drawing denote the same, similar, or equivalentfunctionality, components, or blocks.

FIG. 1 illustrates a general block diagram of a PLD that may be designedor used via illustrative embodiments.

FIG. 2 depicts a floor-plan of a PLD that one may design or implement byusing the disclosed concepts.

FIG. 3 shows various software modules that PLD CAD software according toillustrative embodiments uses.

FIG. 4 illustrates a simplified flowchart for assignment oftiles/regions of an IC according to an exemplary embodiment.

FIG. 5 depicts a simplified flowchart of a technique for applyingguardband according to an exemplary embodiment.

FIG. 6 illustrates a simplified flowchart of a technique for applying alow-power delay model according to an exemplary embodiment.

FIG. 7 shows a simplified flowchart of a technique for increasing therelative weighting according to an exemplary embodiment.

FIG. 8A illustrates a simplified flowchart according to an exemplaryembodiment for optimizing the number of high-speed regions duringplacement and routing by monitoring the regions.

FIG. 8B illustrates a simplified flowchart according to anotherexemplary embodiment for optimizing the number of high-speed regionsduring placement and routing by monitoring the regions.

FIG. 9 depicts a simplified flowchart according to an exemplaryembodiment for determining the mode of operation of one or more regions.

FIG. 10 shows a simplified flowchart according to an exemplaryembodiment for selecting a region for mode conversion.

FIG. 11 illustrates a simplified flowchart according to an exemplaryembodiment that uses a tainting technique.

FIG. 12 shows a block diagram of an exemplary system for processinginformation according to the disclosed concepts.

DETAILED DESCRIPTION

The disclosed concepts relate to apparatus and methods for poweroptimization in electronic circuits, such as programmable logic devices(PLDs). One aspect of the disclosed concepts concerns setting attributesof regions or blocks or tiles of a semiconductor chip or IC.

In some logic devices, regions (or tiles) of the chip can bere-configured to operate in lower-power modes. The cost of these modesof operation is that the logic and/or routing may operate more slowly.

Ideally, a computer-aided design (CAD) tool would try to minimizedynamic and/or static power by configuring many regions to low-powermode, leaving the timing critical portions of the design in high-speedmode. The CAD tool should also support power constraints, which willlimit the power of the final solution, but may impact the timingperformance of the design. It is also desirable that the high-speedlow-power tile optimization algorithm execute in reasonable time.Finally, the CAD tool should optimize the placement and routing solutionto maximize the number of opportunities for regions to be configured tolow-power mode.

As noted above, one may apply the disclosed concepts to a wide varietyof ICs, including PLDs. Without a loss of generality, the followingparagraphs describe the application of disclosed concepts to PLDs. Aspersons of ordinary skill in the art who have the benefit of thedescription of the disclosed concepts understand, however, one may applythe disclosed concepts to other electronic circuits or ICs.

FIG. 1 depicts a general block diagram of a PLD that may be designed orused via illustrative embodiments. One may use the disclosed concepts inthe CAD software that a user may use to program the PLD or for using thePLD, for example, using the PLD's resources to implement a desiredcircuit or system.

Referring to FIG. 1, PLD 103 includes configuration circuitry 130,configuration memory (CRAM) 133, control circuitry 136, programmablelogic 106, programmable interconnect 109, and I/O circuitry 112. Inaddition, PLD 103 may include test/debug circuitry 115, one or moreprocessors 118, one or more communication circuitry 121, one or morememories 124, one or more controllers 127, and initialization circuit139, as desired.

Note that the figure shows a simplified block diagram of PLD 103. Thus,PLD 103 may include other blocks and circuitry, as persons of ordinaryskill in the art understand. Examples of such circuitry include clockgeneration and distribution circuits, redundancy circuits, and the like.Furthermore, PLD 103 may include, analog circuitry, other digitalcircuitry, and/or mixed-mode circuitry, as desired.

Programmable logic 106 includes blocks of configurable or programmablelogic circuitry, such as look-up tables (LUTs), product-term logic,multiplexers (MUXs), logic gates, registers, memory, and the like.Programmable interconnect 109 couples to programmable logic 106 andprovides configurable interconnects (coupling mechanisms) betweenvarious blocks within programmable logic 106 and other circuitry withinor outside PLD 103.

Control circuitry 136 controls various operations within PLD 103. Underthe supervision of control circuitry 136, PLD configuration circuitry130 uses configuration data (which it obtains from an external source,such as a storage device, a host, etc.) to program or configure thefunctionality of PLD 103. Configuration data are typically stored inCRAM 133. The contents of CRAM 133 determine the functionality ofvarious blocks of PLD 103, such as programmable logic 106 andprogrammable interconnect 109. Initialization circuit 139 may cause theperformance of various functions at reset or power-up of PLD 103.

I/O circuitry 112 may constitute a wide variety of I/O devices orcircuits, as persons of ordinary skill in the art who have the benefitof the disclosure understand. I/0 circuitry 112 may couple to variousparts of PLD 103, for example, programmable logic 106 and programmableinterconnect 109. I/O circuitry 112 provides a mechanism and circuitryfor various blocks within PLD 103 to communicate with external circuitryor devices.

Test/debug circuitry 115 facilitates the testing and troubleshooting ofvarious blocks and circuits within PLD 103. Test/debug circuitry 115 mayinclude a variety of blocks or circuits known to persons of ordinaryskill in the art who have the benefit of the disclosure. For example,test/debug circuitry 115 may include circuits for performing tests afterPLD 103 powers up or resets, as desired. Test/debug circuitry 115 mayalso include coding and parity circuits, as desired.

PLD 103 may include one or more processors 118. Processor 118 may coupleto other blocks and circuits within PLD 103. Processor 118 may receivedata and information from circuits within or external to PLD 103 andprocess the information in a wide variety of ways, as persons skilled inthe art with the benefit of the disclosure in this document appreciate.One or more of processor(s) 118 may constitute a digital signalprocessor (DSP). DSPs allow performing a wide variety of signalprocessing tasks, such as compression, decompression, audio processing,video processing, filtering, and the like, as desired.

PLD 103 may also include one or more communication circuits 121.Communication circuit(s) 121 may facilitate data and informationexchange between various circuits within PLD 103 and circuits externalto PLD 103, as persons of ordinary skill in the art who have the benefitof the disclosure in this document understand.

PLD 103 may further include one or more memories 124 and one or morecontroller(s) 127. Memory 124 allows the storage of various data andinformation (such as user-data, intermediate results, calculationresults, etc.) within PLD 103. Memory 124 may have a granular or blockform, as desired. Controller 127 allows interfacing to, and controllingthe operation and various functions of circuitry outside the PLD. Forexample, controller 127 may constitute a memory controller thatinterfaces to and controls an external synchronous dynamic random accessmemory (SDRAM), as desired.

As noted, PLD 103 includes a number of blocks of programmable resources.Implementing a design using those resources often entails placement ofthose blocks (described below) within PLD 103's floorplan. FIG. 2 showsa floor-plan of a PLD that one may design or implement by using thedisclosed concepts. A block, part of a block, or a set of blocks mayconstitute a tile or region of PLD 103.

PLD 103 includes programmable logic 106 arranged as a two-dimensionalarray. Programmable interconnect 109, arranged as horizontalinterconnect and vertical interconnect, couples the blocks ofprogrammable logic 106 to one another. One may place the blocks in aparticular manner so as to implement a user's design, as persons ofordinary skill in the art who have the benefit of the disclosure in thisdocument understand.

In illustrative embodiments, PLD 103 has a hierarchical architecture. Inother words, each block of programmable logic 106 may in turn includesmaller or more granular programmable logic blocks or circuits. Forexample, in one embodiment, programmable logic 106 may constitute blocksof configurable logic named logic array block (LAB), and each LAB mayinclude logic elements (LEs) or other circuitry, as desired.

Persons of ordinary skill in the art who have the benefit of thisdisclosure understand, however, that a wide variety of otherarrangements, with varying terminology and topology, are possible, andfall within the scope of the disclosed concepts. Furthermore, althoughFIG. 4 shows blocks of programmable logic 106, one may use PLDs withother or additional blocks (e.g., memory, processors, other blocks inFIG. 3, etc.) in their floorplans and take advantage of the disclosedconcepts, as persons of ordinary skill in the art who have the benefitof this disclosure understand.

Regardless of the particular arrangement or design, however, one may usethe disclosed concepts in CAD software or programs to exploit the PLD'sresources and implement a desired circuit or system. Implementing auser's design in a PLD, such as PLD 103, entails a number of steps orprocesses, as detailed below.

FIG. 3 illustrates various software modules that PLD CAD softwareaccording to illustrative embodiments uses. The modules includedesign-entry module 203, synthesis module 206, place-and-route module209, tile-selection module 210, and verification module 212. Thefollowing description provides a simplified explanation of the operationof each module.

The CAD techniques may have a variety of applications, as persons ofordinary skill in the art who have the benefit of this disclosureunderstand. Examples include design area, timing performance, powerrequirements, and routability, as desired.

Design-entry module 203 allows the editing of various design descriptionfiles using graphical or textual descriptions of a circuit or itsbehavior, such as schematics, hardware description languages (HDL), orwaveforms, as desired. The user may generate the design files by usingdesign-entry module 203 or by using a variety of electronic designautomation (EDA) or CAD tools (such as industry-standard EDA tools), asdesired. The user may enter the design in a graphic format, awaveform-based format, a schematic format, in a text or binary format,or as a combination of those formats, as desired.

Synthesis module 206 accepts the output of design-entry module 203.Based on the user-provided design, synthesis module 206 generatesappropriate logic circuitry that realizes the user-provided design. Oneor more PLDs (not shown explicitly), such as PLD 103 in FIG. 1,implement the synthesized overall design or system.

Synthesis module 206 may also generate any glue logic that allowsintegration and proper operation and interfacing of various modules inthe user's designs. For example, synthesis module 206 providesappropriate hardware so that an output of one block properly interfaceswith an input of another block. Synthesis module 206 may provideappropriate hardware so as to meet the specifications of each of themodules in the overall design or system.

Furthermore, synthesis module 206 may include algorithms and routinesfor optimizing the synthesized design. Through optimization, synthesismodule 206 seeks to more efficiently use the resources of the one ormore PLDs that implement the overall design or system. Synthesis module206 provides its output to place-and-route module 209. Followingsynthesis, one may include a technology mapping module (not shownexplicitly).

Place-and-route module 209 uses the designer's timing specifications toperform optimal logic mapping and placement. The logic mapping andplacement determine the use of logic resources within the PLD(s). By theuse of particular programmable interconnects with the PLD(s) for certainparts of the design, place-and-route module 209 helps optimize theperformance of the overall design or system. By the proper use of PLDrouting resources, place-and-route module 209 helps to meet the criticaltiming paths of the overall design or system.

Place-and-route module 209 optimizes the critical timing paths to helpprovide timing closure faster in a manner known to persons of ordinaryskill in the art with the benefit of this disclosure. As a result, theoverall design or system can achieve faster performance (i.e., operateat a higher clock rate or have higher throughput).

Tile or region selection module 210 configures various tiles in the IC.In other words, tile-selection module 210 assigns a tile or a group oftiles to operate in the low-power or high-speed modes of operation, asdescribed below in detail.

Verification module 212 performs simulation and verification of thedesign. The simulation and verification seek in part to verify that thedesign complies with the user's prescribed specifications. Thesimulation and verification also aim at detecting and correcting anydesign problems before prototyping the design. Thus, verification module212 helps the user to reduce the overall cost and time-to-market of theoverall design or system.

Verification module 212 may support and perform a variety ofverification and simulation options, as desired. The options may includefunctional verification, test-bench generation, static timing analysis,timing simulation, hardware/software simulation, in-system verification,board-level timing analysis, signal integrity analysis andelectro-magnetic compatibility (EMC), formal netlist verification, andthe like, as persons of ordinary skill in the art who have the benefitof the description of this disclosure understand.

Note that one may perform other or additional verification techniques asdesired and as persons of ordinary skill in the art who have the benefitof this disclosure understand. Verification of the design may also beperformed at other phases in the flow, as appropriate, and as desired.

As noted, the disclosed concepts may use a CAD flow, such as the CADflow shown in FIG. 3. Generally speaking, one aspect of the disclosedconcepts assign attributes to various tiles/regions of an IC that affectits power consumption and, hence, overall performance. FIG. 4 shows asimplified flowchart for configuration of tiles/regions of an ICaccording to an exemplary embodiment.

At 250, the IC's specifications are received. The specifications mayinclude physical specifications, electronic specifications, and thelike, as persons of ordinary skill in the art who have the benefit ofthe description of the disclosed concepts understand. At 252,performance specifications for the IC are received. The performancespecifications may include timing specifications, power specifications,and the like, as persons of ordinary skill in the art who have thebenefit of the description of the disclosed concepts understand.

At 254, attributes for various regions of the IC are assigned. Morespecifically, and generally speaking, one may assign a given region, ora group of regions, as high-speed or low-power, as desired. At 256, theeffect of the assignment of the regions is evaluated. To do so, one maysimulate or characterize (or use other suitable technique, as persons ofordinary skill in the art who have the benefit of the description of thedisclosed concepts understand) the performance of the IC.

Some embodiments according to the disclosed concepts relate to methodsand algorithms that may run after placement and routing (see FIG. 3 forCAD flow) to determine which regions should operate in high-speed orlow-power mode. Before describing those techniques in detail, somemodifications to synthesis, placement, and routing according to thedisclosed concepts are described below.

In some embodiments, synthesis downsizes non-critical logic, increasingits delay but decreasing its area cost until it is near critical. Tofacilitate configuration of more logic to operate in the low-power mode,synthesis may be biased to favor solutions that have unbalanced pathcriticalities creating more opportunities for low-power operation. Notethat even though doing so may result in solutions with more logicelements, it may result in lower power consumption if it results in lesslogic operating in the high-speed mode.

In some embodiments, the placement and routing engines use a delay modelthat corresponds to the high-speed mode of operation. Put another way,the assumption is that all the critical logic and routing will beconfigured to operate in high-speed mode. Hence, the high-speed mode ofoperation should be assumed during timing optimization for the besttiming results.

Some placement and routing algorithms will terminate early or reduceeffort when timing is met. That result can leave a lot of critical logicand routing that has to be configured to the high-speed mode ofoperation. To avoid this situation, a guardband can be applied toreflect the delay difference between high-speed and low-power modes ofoperation. That way, the placement and routing engines will get themargin necessary to enable more regions to operate in low-power mode.The margin can also be important for timing in compiles that haveconstraints on power (some regions may have to be left in low-power,even though they contain critical logic).

FIG. 5 shows a simplified flowchart of a technique for applyingguardband according to an exemplary embodiment. At 270, placement androuting is performed. After the placement and routing, or as part ofplacement and routing, at 272 a guardband is applied. The guardbandreflects the delay difference between high-speed and low-power modes ofoperation, as described above.

Alternatively, a low-power mode delay model can be used to achievesimilar results to a guardband. Because the relative delays of resourcesin this low-power model may not match those of the high-speed model,however, there may be some timing degradation with this approach. Thatsaid, using the low-power mode delay model does provide some poweradvantage by optimizing the placement and routing to meet timingassuming configuration (and relative delays) in low-power mode.

FIG. 6 shows a simplified flowchart of a technique for applying alow-power delay model according to an exemplary embodiment. At 270,placement and routing is performed. After the placement and routing, oras part of placement and routing, at 274 the placement and routing isoptimized by applying a low-power delay model, as described above.

To further reduce the number of regions that need to be configured tohigh-speed mode, the placement and routing algorithm can be instructedto more aggressively optimize near-critical paths (the paths that arenot highly timing critical, but have low margin). This can be done byincreasing the relative weighting on the respective connections. Forexample, if the placement and/or routing algorithm uses connectioncriticalities (between 0 and 1, indicating the criticality of eachconnection), applying an exponent less than one to these criticalities,will increase the relative criticality of the near-critical paths.

FIG. 7 shows a simplified flowchart of a technique for increasing therelative weighting according to an exemplary embodiment. At 270,placement and routing is performed. After the placement and routing, oras part of placement and routing, at 278 the near-critical paths areoptimized by increasing the relative weighting of the respectiveconnections, as described above.

To further reduce the number of regions that need to be configured tohigh-speed mode, the placement and routing algorithm can be modified tomonitor the regions that are likely to be made high-speed.

In order to achieve this, it may be necessary to compute the probabilitythat a given resource (or group of resources) will demand a region beset to high-speed (or use a region that is set to operate in thehigh-speed mode of operation). If the speed difference betweenhigh-speed and low-power resources is typically X %, and all the pathsgoing through the given resource are more than X % off from criticalvalue(s), the probability that it will demand high-speed operation iszero.

On the other hand, if a resource is on a critical path, the probabilitythat it will demand high-speed operation is unity. All the probabilitiesin between can be computed (linearly) based on the criticality of thepaths going through the resource. This is a relatively simple model ofthe probability that a resource will demand the high-speed mode ofoperation. One may use other models, as persons of ordinary skill in theart who have the benefit of the description of the disclosed conceptsunderstand. For example, other models may also consider the delays ofthe resources, how many critical paths go through the resources, theprobabilities for the high-speed mode of operation of other resources,and how the resources along the same path are distributed betweenhigh-speed low-power regions.

FIG. 8A shows a simplified flowchart according to an exemplaryembodiment for optimizing the number of high-speed regions duringplacement and routing by monitoring the regions. At 302, the probabilitythat a given set of resources will need the high-speed setting (i.e.,the high-speed mode of operation) is computed. At 304, the probabilitythat the corresponding regions will need the high-speed setting iscomputed.

Once the resource probabilities are computed, at 306 they can be used tocompute the probability that a region will end up using the high-speedmode of operation. For example, the probability that a region will endup using the low-power mode of operation can be assumed to be equal tothe product of the probabilities that all the resources in the regionwill be low-power. The probability that a region will be high-power issimply one minus the probability that the region will be low-power.

The above model is a relatively simple model of the probability that aregion will demand high-speed mode. One may use other models, asdesired, and as persons of ordinary skill in the art who have thebenefit of the description of the disclosed concepts understand. Forexample, models may also consider the delays of the resources, how manycritical paths go through the resources, the power benefit of low-powermode, the high-speed probabilities of other regions, and how theresources along the same path are distributed between high-speedlow-power regions.

Given the region probabilities, at 306 a cost (or several costs) can becomputed to penalize solutions (for example, placement solutions) thathave a relatively large number of high-speed regions and/or a largeexpected power consumption. One may do so in a number of ways, asdesired, as persons of ordinary skill in the art who have the benefit ofthe description of the disclosed concepts understand.

At 308, one or more placement or routing alternatives are proposed. At310, the probabilities and the cost are incrementally updated based onthe proposed alternative(s) in order to evaluate the proposedalternative(s). At 312, a check is made whether the operation hasfinished (e.g., no more proposed alternatives exist). If not, controlreturns to 308, and additional alternative(s) are proposed.

FIG. 8B shows a simplified flowchart according to another exemplaryembodiment for optimizing the number of high-speed regions duringplacement and routing by monitoring the regions. At 302, the probabilitythat a given set of resources will need the high-speed setting (i.e.,the high-speed mode of operation) is computed. At 304, the probabilitythat the corresponding regions will need the high-speed setting iscomputed.

Once the resource probabilities are computed, at 304 they can be used tocompute the probability that a region will end up using the high-speedmode of operation, similar to the embodiment in FIG. 8A, describedabove. At 314, given the region probabilities, costs can be computedthat would penalize changes that would increase the likelihood that aregion would have to use the high-speed mode of operation. For example,a cost proportional to the probability that a region is a low-powerregion multiplied by the probability of a connection using the resourcewill demand the high-speed mode of operation can be used to discouragethe router from selecting resources for a critical connection in regionsthat are likely to end up in the low-power mode. The cost may alsoinclude a component that considers the power change from the high-speedmode to the low-power mode. This component may be incorporated throughsimple multiplication.

At 316, the probability data are updated to reflect any change(s) madeto the placement or routing. At 312, a check is made whether theoperation has finished (e.g., no more proposed alternatives exist). Ifnot, control returns to 308, and additional alternative(s) are proposed.

According to another aspect of the disclosed concepts, in exemplaryembodiments, an algorithm or operation runs after placement and routing(see FIG. 3) that chooses which regions should operate in the high-speedor low-power modes of operation (i.e., tile or region selection). FIG. 9depicts a simplified flowchart according to an exemplary embodiment fordetermines the mode of operation of one or more regions. At 320, allregions are set to the low-power mode of operation, except constrainedregions that should operate in high-speed mode (in order to ensureproper operation and timing).

Next, a set of iterations are performed. During each iteration, thealgorithm re-configures some tiles from the low-power mode to thehigh-speed mode. In each iteration, a long-path timing analysis(potentially with guardband to achieve a desired margin) is performed at322, using delays based on the current regions' high-speed or low-powermode settings.

All low-power regions with failing paths are considered as candidatesfor high-speed mode re-configuration. To help determine which regionsshould be re-configured, a gain score is assigned to each region. Thus,at 324, gain scores are computed or updated for each region.

The gain score of a region can be a function of the negative slackimprovement that results from re-configuring the respective region inisolation. This negative slack improvement can be estimated on aper-resource basis by considering a quantity A, where:A=min((low-power mode delay)−(high-speed mode delay),max(0,−(slackthrough resource))).

Put another way, the negative slack through a resource cannot beimproved by more than the magnitude of the negative slack and the changein the resource delay. The negative slack improvement of the tile can beestimated as the sum of the respective resource negative slackimprovements of the tile.

One may use better estimates of negative slack improvement of a tile byconsidering a combination of resources, and how the total delay changeaffects the negative slack of each relevant path. A relatively quickestimate of the effect a resource will have on multiple paths can becomputed by multiplying the quantity A (see above) and the failing pathcount through the resource. The failing path count for each timing edge(resource) can be estimated/computed by using a standard path-countingalgorithm or technique, but applying it to merely the portion of thetiming graph with negative slack edges.

Once the negative slack improvement of a region is computed, it can benormalized. To do so, one divides the negative slack by the magnitude ofthe power impact of changing the region to high-speed mode to computethe final gain score.

At 326, some tiles or regions are changed to the high-speed mode ofoperation. As a refinement, one may select the region with the highestgain score as the best candidate to switch to high-speed mode. FIG. 10shows a simplified flowchart according to an exemplary embodiment forselecting a region for mode conversion according to this refinement. At340, gains of various regions are computed/updated. For the mostconservative style of optimization (i.e., minimum number of high-speedtiles), the highest gain score region is re-configured. At 342, theregion with the highest gain score is converted to the high-speed modeof operation. At 344, a timing analysis (e.g., an incremental timinganalysis) can then be performed to propagate (figure out) the effect ontiming of the change in the region's mode of operation.

The gain of all the regions that contain resources that are affected bythese timing changes can be re-computed. Note that to make theoperations fast and incremental, data caching may be used. For example,one may cache the timing edges related to each region. Similarly, onemay cache the regions related to each timing edge. After re-computingthe gains, the region with the highest gain score can then be processed,and so on, until no more low-power mode regions have failing timingpaths.

Referring to FIG. 9, at 328, one may optionally convert (described inmore detail below) some tiles back to the low-power mode of operation.One may then perform a timing analysis to evaluate the change. At 330, acheck is made to determine whether the operation has finished (e.g., nomore changes remain). If not, control passes to 322, and the iterationscontinue.

As an alternative to timing analyzing after each region is converted,one may use the approach of marking all the regions that have “tainted”or stale gain scores because their gains can be affected by regionre-configurations elsewhere in the design. This “tainting” can beefficiently achieved by doing local traversals starting with the timingedges relevant to a converted region.

FIG. 11 shows a simplified flowchart according to an exemplaryembodiment that uses the tainting technique. Similar to FIG. 10,described above, at 340 gains of various regions are computed/updated.At 342, the region with the highest gain score is converted to thehigh-speed mode of operation.

After every region is converted, at 370 the “tainting” process can beexecuted. The next highest-gain score “untainted” or unstale region canbe then converted at 372. This process can then be repeated (at 374)until there are no more “untainted” or unstale regions, in which case, atiming analysis can be performed, then all the “tainting” or stalenesscan be removed, and the overall process repeated.

Note that during the “tainting,” one should expand the “taint” orstaleness from “tainted” or stale regions as well, in addition to theconverted regions, because removing a region as a candidate forconversion, means that the timing paths through this region can be in adifferent high-speed/low-power mode than optimal. That is, a “tainted”or stale region may need to be converted to achieve an optimal solution,so other regions should not be processed if they are dependent on thisregion, until this region gets an opportunity to be processed.

A less conservative style of optimization can be used to save runtime.Instead of just converting the highest gain “untainted” or unstaleregions between timing analyses, an embodiment of the method can ensurethat N regions are converted between timing analyses. If there are notenough “untainted” or unstale regions to achieve this, “tainted” orstale regions with the highest gain can be considered. The value of Ncan be based on the number of iterations being performed and the numberof regions with gains (being considered for conversion). That is, ifthere are I iterations left to be performed (including the current one),and there are C candidate regions, N can be set to C/I. Given that Cwill likely decrease by more than N per iteration (failing pathsbeginning to pass timing), N can be set lower than this value in earlieriterations to reduce the number of regions “inappropriately” converted.

Referring to 328 in FIG. 9, one option if regions are converted fromlower power to high speed where they should not have been converted (orhave been converted unnecessarily) is to have a post-processing stepthat converts high-speed regions back to low-power regions (see 328 inFIG. 9). This step can also be interleaved with the low-power tohigh-speed conversion iterations, so that the algorithm does notgradually increase the number of high-speed regions, but oscillatesuntil an improved or good final solution is obtained.

One consideration when converting from high-speed to low-power (whichmotivates the opposite direction of conversion in the originalembodiment) is that it is relatively expensive (not trivial) toperfectly predict whether the conversion of the tile will cause a timingdegradation. The effect of this type of imprecision on the originalembodiment is to convert more tiles to high-speed, which affects power.

In practice, timing constraints are “harder” than power constraints, andthe impact on power is generally relatively small, so the embodiment inFIG. 9 primarily converts from low-power to high-speed. To avoid thisimprecision, one may perform an incremental timing analysis anticipatinga region change from high-speed to low-power, or do the change, performan incremental analysis, and undo the change if it proves detrimental tothe timing.

Alternatively, the change can be made and, if timing is degraded,iterations of low-power to high-speed can be invoked to remedy thesituation. Also note that high-speed to low-power and low-power tohigh-speed re-configurations may be combined in a single iteration, asdesired. These approaches can be relatively expensive (in terms of timeor computing resources) but, if they are used judiciously, the expensemay be manageable and may end up reducing the number of high-speedregions and/or power.

Note that similar techniques to those described above can be used tocompute gain scores for regions when converting from high-speed tolow-power. Generally, the gain (or cost) function should discouragetiles from being changed if they have low slack, large high-speed tolow-power delay differentials or differences, a relative large number offailing or close-to-failing paths, and/or small power savings from achange of mode (i.e., a relatively small difference between the powerconsumption of the tile in the low-power and high-speed modes ofoperation).

Most timing analyzers annotate slacks on data-path connections. Clockpaths also affect timing. Therefore, various embodiments may reconfigureto the high-speed mode of operation some regions that contain clockpaths in order to satisfy design timing constraints. To achieve thisgoal, some embodiments may take the long-path data path slacks at theoutput of storage elements, and propagate those slacks backward alongthe corresponding clock paths that feed the storage elements.

This slack propagation involves setting a clock-edge slack to theminimum of its current slack and the slack being propagated. That way,the relevant clock paths receive the appropriate or necessary slacks toguide optimization, as described above.

Alternatively, the timing analysis can analyze paths starting at clocksources, through source storage elements, to the destination storageelements. That way, slacks will be calculated for source clock paths inaddition to data paths. To compute slacks for the clock paths to thedestination storage elements, a desired, specified, or requiredtraversal can be performed from the destination register to the clocksources, assuming that the destination has a minimum required,specified, or desired time equal to the arrival time at the destinationregister.

Note that for a long-path constraint, the slacks computed for the clockpath to the destination register will be short-path slacks. Long-pathoptimization benefits from a longer clock delay to the destinationregister.

Similar techniques can be used to handle short-path constraints, asdesired. For example, short-path data path slacks at the input ofstorage elements can be propagated (as long-path slacks) backward alongthe corresponding clock paths that feed the storage elements.

Alternatively, for short-path constraints, to compute long-path slacksfor the clock paths to the destination storage elements, a required ordesired traversal can be performed from the destination register to theclock sources assuming that the destination has a maximum required,desired, or specified time equal to the arrival time at the destinationregister.

It can also be desirable or important that exemplary embodimentsaccording to the disclosed concepts tolerate impossible or unachievabletiming constraints gracefully. That is, the user sometimes sets timingconstraints that are impossible to meet in order to get the bestpossible timing results. It would be undesirable if all the used regionswere set to high-speed mode because, in reality, the clock can run asfast as the most critical path. So, as long as the most critical pathuses resources in regions that are all high-speed, there is no real needto speed up other paths.

To achieve this goal, slack shifting can be beneficial. That is, slacks,on a per-timing-domain basis, can be shifted, so that, at most, pathswithin X % of critical have slacks less than or equal to zero. Doing solimits the candidates for high-speed mode to those paths that are nearcritical (within X %).

To achieve the minimum number of high-speed regions, X can be set closeto zero. Larger values of X can be used to compensate for delay modelingerrors. That is, if the delay model can be inaccurate by up to, say, 5%,to achieve the best timing results, X should be set to five to ensurethat a path within 5% of the delay of the critical path uses allhigh-speed resources, because it could, in fact, be critical. In otherembodiments, the timing achieved with all tiles set to high-speed can beextracted and re-applied as timing constraints (perhaps with extramargin) to guide high-speed low-power region optimization to a solutionthat achieves maximum performance without increasing power appreciablyor to a relatively large extent.

To support constraints on the number of high-speed regions allowed, oron the maximum power, various embodiments according to the disclosedconcepts may restrict the regions converted. This restriction can beachieved by limiting, in each iteration, the number of candidate regionsto the appropriately-sized subset with the highest gains.

Slack shifting can be beneficial in these instances because, if alltiming failures cannot be fixed, it is generally beneficial to fix orcorrect the most serious timing failures (the most critical paths).Recall that, as discussed above, slack shifting adjusts slacks untilpaths that are within X % of critical have slacks less than or equal tozero. For a given value of X, a certain number of candidate regions willbe identified based on which timing failures remain. By reducing thevalue of X, the number of candidate regions can be reduced to bettermeet the restrictions on how many more high-speed regions are allowed,and/or how much more power increase can be tolerated. Thus, someembodiments will try to reduce the value of X to ensure that the subsetof regions with the highest gains that are chosen as candidates willcontain the most critical paths in the design.

It should be noted that even though two modes of operation (low-powerand high-speed) are discussed, these techniques can be easily extendedto support multiple modes of operation. To achieve multiple modes ofoperation, the same placement and routing techniques discussed above canbe applied by simply assuming that just the highest speed and lowestpower modes are available. That way, the placement and routing will beoptimized to minimize the number of high-speed regions and maximize thenumber of low power regions in a coarse-grained fashion. The fine tuningcan be left to the high-speed low-power optimization algorithm.

In the high-speed low-power optimization algorithm, instead of justswitching directly from low-power to high-speed modes, the regions couldbe re-configured to their adjacent settings (adjacent modes ofoperation). For example, if the current setting of a region islow-power, and the algorithm seeks to increase the speed of the region,it can change the region from low-power to medium-speed in oneiteration.

In another iteration, it can change the region from medium-speed tohigh-speed, if necessary or desired. The gains may be computed based onthe better or more advantageous of the changes, e.g., changing fromlow-power to medium-speed and low-power to high-speed. That way, thegains reflect the fact that the medium-speed setting may be temporary.

Alternatively, separate gains can be computed for all the regionre-configuration options. For example, a separate gain can be computedfor going from low-power to medium-speed, and a separate gain can becomputed for going from low-power to high-speed. The better or moreadvantageous of the two re-configurations can be seamlessly picked asregion selection is performed using gains.

As noted above, although the above description concerns in parts theapplication of the disclosed concepts to PLDs, one may apply thedisclosed concepts to a variety of other electronic circuits anddevices, by making modifications that fall within the knowledge ofpersons of ordinary skill in the art who have the benefit of thedescription of the disclosed concepts. Some examples of such devicesinclude custom, standard-cell, gate-array, field-programmable gatearrays (FPGAs), and structured application specific integrated circuit(ASIC) implementations.

One may run or execute the disclosed algorithms, methods, or software oncomputer systems or processors. FIG. 12 shows a block diagram of anexemplary system for processing information according to the disclosedconcepts. Persons of ordinary skill in the art who have the benefit ofthe disclosure understand that one may use a wide variety of othercomputer systems, processors, microcomputers, workstations, and thelike, as desired.

System 1000 includes a computer device 1005, an input device 1010, avideo/display device 1015, and a storage/output device 1020, althoughone may include more than one of each of those devices, as desired.

Computer device 1005 couples to input device 1010, video/display device1015, and storage/output device 1020. System 1000 may include more thatone computer device 1005, for example, a set of associated computerdevices or systems, as desired, and as persons of ordinary skill in theart who have the benefit of the description of the disclosed conceptsunderstand.

System 1000 operates in association with input from a user. The userinput typically causes system 1000 to perform specific desiredinformation-processing tasks, including circuit simulation. System 1000in part uses computer device 1005 to perform those tasks. Computerdevice 1005 includes an information-processing circuitry, such as acentral-processing unit (CPU), although one may use more than one CPU orinformation-processing circuitry, as persons skilled in the art wouldunderstand.

Input device 1010 receives input from the user and makes that inputavailable to computer device 1005 for processing. The user input mayinclude data, instructions, or both, as desired. Input device 1010 mayconstitute an alphanumeric input device (e.g., a keyboard), a pointingdevice (e.g., a mouse, roller-ball, light pen, touch-sensitiveapparatus, for example, a touch-sensitive display, or tablet), or both.The user operates the alphanumeric keyboard to provide text, such asASCII characters, to computer device 1005. Similarly, the user operatesthe pointing device to provide cursor position or control information tocomputer device 1005.

Video/display device 1015 displays visual images to the user. The visualimages may include information about the operation of computer device1005, such as graphs, pictures, images, and text. The video/displaydevice may constitute a computer monitor or display, a projectiondevice, and the like, as persons of ordinary skill in the art wouldunderstand. If a system uses a touch-sensitive display, the display mayalso operate to provide user input to computer device 1005.

Storage/output device 1020 allows computer device 1005 to storeinformation for additional processing or later retrieval (e.g.,softcopy), to present information in various forms (e.g., hardcopy), orboth. As an example, storage/output device 1020 may constitute amagnetic, optical, or magneto-optical drive capable of storinginformation on a desired medium and in a desired format. As anotherexample, storage/output device 1020 may constitute a printer, plotter,or other output device to generate printed or plotted expressions of theinformation from the computer device 1005.

Computer-readable medium 1025 interrelates structurally and functionallyto computer device 1005. Computer-readable medium 1025 stores, encodes,records, and/or embodies functional descriptive material. By way ofillustration, the functional descriptive material may include computerprograms, computer code, computer applications, and/or informationstructures (e.g., data structures or file systems). When stored,encoded, recorded, and/or embodied by computer-readable medium 1025, thefunctional descriptive material imparts functionality. The functionaldescriptive material interrelates to computer-readable medium 1025.

Information structures within the functional descriptive material definestructural and functional interrelations between the informationstructures and computer-readable medium 1025 and/or other aspects ofsystem 1000. These interrelations permit the realization of theinformation structures' functionality. Moreover, within such functionaldescriptive material, computer programs define structural and functionalinterrelations between the computer programs and computer-readablemedium 1025 and other aspects of system 1000. These interrelationspermit the realization of the computer programs' functionality.

By way of illustration, computer device 1005 reads, accesses, or copiesfunctional descriptive material into a computer memory (not shownexplicitly in the figure) of computer device 1005. Computer device 1005performs operations in response to the material present in the computermemory. Computer device 1005 may perform the operations of processing acomputer application that causes computer device 1005 to performadditional operations. Accordingly, the functional descriptive materialexhibits a functional interrelation with the way computer device 1005executes processes and performs operations.

Furthermore, computer-readable medium 1025 constitutes an apparatus fromwhich computer device 1005 may access computer information, programs,code, and/or applications. Computer device 1005 may process theinformation, programs, code, and/or applications that cause computerdevice 1005 to perform additional operations.

Note that one may implement computer-readable medium 1025 in a varietyof ways, as persons of ordinary skill in the art would understand. Forexample, memory within computer device 1005 may constitute acomputer-readable medium 1025, as desired. Alternatively,computer-readable medium 1025 may include a set of associated,interrelated, coupled (e.g., through conductors, fibers, etc.), ornetworked computer-readable media, for example, when computer device1005 receives the functional descriptive material from a network ofcomputer devices or information-processing systems. Note that computerdevice 1005 may receive the functional descriptive material fromcomputer-readable medium 1025, the network, or both, as desired.

Referring to the figures, persons of ordinary skill in the art will notethat the various blocks shown may depict mainly the conceptual functionsand signal flow. The actual circuit implementation may or may notcontain separately identifiable hardware for the various functionalblocks and may or may not use the particular circuitry shown. Forexample, one may combine the functionality of various blocks into onecircuit block, as desired. Furthermore, one may realize thefunctionality of a single block in several circuit blocks, as desired.The choice of circuit implementation depends on various factors, such asparticular design and performance specifications for a givenimplementation, as persons of ordinary skill in the art who have thebenefit of the disclosure in this document understand. Othermodifications and alternative embodiments of the disclosed concepts inaddition to those described here will be apparent to persons of ordinaryskill in the art who have the benefit of the description of thedisclosure. Accordingly, this description teaches those skilled in theart the manner of carrying out the disclosed concepts and are to beconstrued as illustrative only.

The forms of the disclosed concepts and embodiments shown and describedshould be taken as the presently preferred or illustrative embodiments.Persons skilled in the art may make various changes in the shape, sizeand arrangement of parts without departing from the scope of thedisclosure in this document. For example, persons skilled in the art maysubstitute equivalent elements for the elements illustrated anddescribed here. Moreover, persons skilled in the art who have thebenefit of this disclosure may use certain features of the disclosedconcepts independently of the use of other features, without departingfrom the scope of the disclosure.

The invention claimed is:
 1. A system for computer-aided design (CAD) ofan integrated circuit (IC) to implement a user's design by usingresources of the integrated circuit (IC), the system comprising acomputer, configured to optimize synthesis, placement, and/or routing ofthe integrated circuit (IC) by maximizing a number of low-power regionsin the integrated circuit (IC), wherein the computer is furtherconfigured to minimize a number of high-speed regions in the integratedcircuit (IC) by monitoring a set of regions in the integrated circuit(IC) that are to be made high-speed regions by computing a firstprobability that a region in the set of regions will use the high-speedmode of operation.
 2. The system according to claim 1, wherein thecomputer is further configured to monitor the set of regions in theintegrated circuit (IC) that are to be made high-speed regions bycomputing a second probability that a connection in the integratedcircuit (IC) will use a region that operates in the high-speed mode ofoperation.
 3. The system according to claim 2, wherein the computer isfurther configured to compute a cost based on the first and secondprobabilities.
 4. The system according to claim 1, wherein the computeris further configured to compute a cost based on the first probability.5. The system according to claim 4, wherein the computer is furtherconfigured to incrementally update the first probability and the cost.6. The system according to claim 1, wherein the computer is furtherconfigured to propose a placement/routing alternative.
 7. Acomputer-implemented method for implementing a user's design usingresources of integrated circuit (IC), the method comprising optimizing,using the computer, synthesis, placement, and/or routing of theintegrated circuit (IC) by maximizing a number of low-power regions inthe integrated circuit (IC), wherein the computer minimizes a number ofhigh-speed regions in the integrated circuit (IC) by monitoring a set ofregions in the integrated circuit (IC) that are to be made high-speedregions by computing a first probability that a region in the set ofregions will use the high-speed mode of operation.
 8. The methodaccording to claim 7, further comprising using the computer to monitorthe set of regions in the integrated circuit (IC) that are to be madehigh-speed regions by computing a second probability that a connectionin the integrated circuit (IC) will use a region that operates in thehigh-speed mode of operation.
 9. The method according to claim 8,further comprising using the computer to compute a cost based on thefirst and second probabilities.
 10. The method according to claim 7,further comprising using the computer to compute a cost based on thefirst probability.
 11. The method according to claim 10, furthercomprising using the computer to incrementally update the firstprobability and the cost.
 12. The method according to claim 7, whereinthe computer proposes a placement/routing alternative.